The present invention relates to a noise reduction system for a passenger compartment of an automotive vehicle by positively generating a sound from a sound source to cancel the vehicle internal noise.
There have been proposed several techniques for reducing the noise sound in the passenger compartment by producing a canceling sound, having the same amplitude as the noise sound and a reversed phase thereto, from a sound source disposed in the passenger compartment.
There are recently vehicle internal techniques for reducing a noise sound noise reduction (Least Means Square) algorithm (a theory by using a LMS filter coefficient by approximating it to for obtaining a means square error in order to simplify an instantaneous that a filter correction formula is a formula, utilizing or by employing a MEFX-LMS (Multiple Error Filtered X-LMS) recursive expression) algorithm. This technique has already been put to a practical use in some of production vehicles.
Commonly, an internal noise reduction system using this LMS algorithm is composed in such a way that: a vibration noise source signal (primary source) is detected from an engine, then the primary source is synthesized with a filter coefficient of an adaptive filter into a canceling sound, then the canceling sound is generated from a speaker to cancel a noise sound in the passenger compartment, further the noise sound reduced by the canceling sound is detected as an error signal by a microphone disposed at a noise receiving point, and based on the detected error signal and a primary source signal synthesized with a speaker microphone transmission characteristic as a finite impulse response, as shown in FIG. 6), a filter coefficient W of the adaptive filter is updated by the LMS algorithm so as to optimize the reduced noise sound at the noise receiving point.
The filter coefficient of the adaptive filter is updated according to the following formula: EQU W.sub.ik+1 =W.sub.ik -.alpha..multidot.e.sub.k .multidot.C.sub.MNO .multidot.X.sub.k-1 ( 1)
where W.sub.ik+1 is a filter coefficient after updating ("i"th order), W.sub.ik is a present filter coefficient, .alpha. is a step size which represents an updating ratio of the filter coefficient, e.sub.k is an error signal, C.sub.MNO is a series of compensation coefficients (C.sub.MNO =[C.sub.O, C.sub.1, C.sub.2, . . . , C.sub.j ]), and X.sub.k is an input signal (X.sub.k =[X.sub.k, X.sub.k-1, X.sub.k-2, . . . , X.sub.k-j+1 ]).
An updating amount of the present filter coefficient W.sub.k becomes large, as the step size .alpha. is set to be large and the updating amount of the present filter coefficient W.sub.k becomes small, as .alpha. is set to be small.
In the noise reduction system using a prior LMS algorithm, when an error signal e.sub.k varies rapidly by the change of the engine operating condition (for example, during acceleration or deceleration), since an engine noise within the passenger compartment varies more than an updating rate of the adaptive filter which is determined by the above step size .alpha., it takes time to update the filter coefficient W.sub.k while following the change of engine noise and to converge at an optimum value.
To overcome this shortfall, as shown in Japanese Patent Application Laid-open No. 178846 (1991) a noise reduction system with a step size which can be varied according to vehicular acceleration or deceleration is proposed. According to this noise reduction system, a larger updating rate of the filter coefficient can be obtained by setting a step size .alpha. at a large value with an increase of vehicular acceleration. Therefore, it takes less time to update the filter coefficient and to converge at an optimum value, compared to the prior noise reduction system.
However, the amount of the filter coefficient W is dependent upon the sequence of the compensation coefficients C.sub.MNO for compensating speaker/microphone transmission characteristics within the passenger compartment, as easily understood in the above formula (1). The sequence C.sub.MNO has a frequency characteristic as shown in FIG. 6, for example. In this example of frequency characteristic, it includes a frequency hard to be transferred from speaker to microphone (frequency B in FIG. 6). For this reason, as indicated in FIG. 7 (a), the filter coefficient W is updated largely at the frequency A but it is updated little at the frequency B, as indicated in FIG. 7 (b). Even in this case shown in FIG. 7 (b), the noise will be reduced gradually by repeated updatings of the filter coefficient W, however, when the noise is sufficiently reduced, the filter coefficient W will grow up into a large value. Once the filter coefficient W grows up into a large value, it takes time for the filter coefficient W to reach an optimum value when the frequency like a frequency B becomes small rapidly due to an abrupt change of engine speed. As a result of this, the insufficiently canceled noise sound will be heard by the driver or passengers during that period.
To solve this problem, it can be considered that the step size .alpha. is to be set at a larger value in the above variable .alpha. system. However, even in this method, it is necessary to set an upper threshold in the filter coefficient W to be updated, because there is a possibility that the noise reduction system will diverge unless otherwise. Therefore, this method can not be an effective way to solve the problem completely.